Le, Trung Thanh and Karim, Abed Meraim and Adel, Hafiane and Nguyen, Linh Trung Sparse Subspace Tracking in High Dimensions. In: ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 7-13 May, 2022, Singapore. (In Press)
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Abstract
We studied the problem of sparse subspace tracking in the high-dimensional regime where the dimension is comparable to or much larger than the sample size. Leveraging power iteration and thresholding methods, a new provable algorithm called OPIT was derived for tracking the sparse principal subspace of data streams over time. We also presented a theoretical result on its convergence to verify its consistency in high dimensions. Several experiments were carried out on both synthetic and real data to demonstrate the effectiveness of OPIT.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Electronics and Communications ISI/Scopus indexed conference |
| Divisions: | Advanced Insitute of Engineering and Technology (AVITECH) |
| Depositing User: | Lê Trung Thành |
| Date Deposited: | 21 Mar 2022 00:30 |
| Last Modified: | 21 Mar 2022 00:30 |
| URI: | http://eprints.uet.vnu.edu.vn/eprints/id/eprint/4712 |
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